Archive for December, 2010

Well here’s an interesting development. According to a Bloomberg report, Microsoft plans to announce a version of Windows that will run on ARM processors for the first time ever.

Assuming Bloomberg’s sources know what they’re talking about, Microsoft will make the stunning announcement at the Consumer Electronics Show in Las Vegas next month. The sources say the specialized version of Windows would be customized for battery-powered devices, like tablet PCs and other handhelds.

This would be great news for ARM, whose stock rose 6.6 percent after word got out, but what about Intel? The upcoming software will also work with Intel and AMD processors, both of which would like to tap into the emerging tablet market. Intel has already made a push with its Atom processor line, but this would clearly benefit ARM more than any other chip maker.

Back in October, Google added the ability to easily change the location from where you search. It’s located just under the search verticals – click on "Change Location," and you’ll see something like the screen below (lower-left):

Obviously, this is of tremendous value to anyone doing local SEO, but given Google’s uneven support for opting out of personalization, I had to wonder whether the location feature was really accurate. If I set my location to another city, would I really see what my clients and prospects were seeing?

Obligatory Disclaimers

What I’m about to describe isn’t the most scientific experiment; it’s just an initial exploration of whether Google’s "Change Location" feature matched up across different cities for different users. Your results may vary. If your experiences differ, we’d love to hear your comments.

The Basic Experiment

I grabbed 3 of the finest minds in SEO (or, at least, that’s what I told them so they’d volunteer) from 3 US cities other than mine (we kept this domestic to avoid any complications from ccTLDs). I’m in Chicago, Joanna is at Moz HQ in Seattle, Michael is in Portland, and Lindsay is in Tampa.

For each city, we picked a one-word query that had a distinct local flavor (suggested by the respective localite). We kept it to the realm of food and drink, because who doesn’t like to eat and drink? The final queries were:

Chicago – "pizza"

Seattle – "coffee"

Portland – "pubs"

Tampa – "seafood"

Each of us started with our own city, ran the query, and recorded two things: (1) where the local search results began, and (2) the URLs for the local search results. If there were 3 organic results prior to the first local result, they started at position 4, for example. The new, integrated results are a bit tricky, but we counted any results with a letter (A)-(G) as a local result, whether it was specifically a "Places" result or not. We repeated the process for each of the 4 cities/queries.

Prior to running searches, we each logged out of our Google accounts. We tested adding the &pws=0 parameter to remove personalization, but there was no case where this had any impact on our results. City order was rotated across the 4 participants.

The Basic Results

I was all set to develop some really complicated math to determine how 2 sets of queries matched each other, but the real results ended up being so black-and-white, that I’ve just created a grid of how the 4 participants’ results matched up. If I had Site X in position (D) and someone else did, too, that’s a match, plain and simple:

The table shows how each person’s results match up to the local user’s results (represented by the city name). The diagonal (grayed-out) is always a 100% match, since that person is the local user. For these searches (being fairly popular), all local results were 7-packs. Chicago, Portland, and Tampa local results started after 3 organic listings (position #4). Seattle local listings started in the #1 position (more on that below).

The short takeaway – Florida is trouble. Our results matched completely, except for Tampa, where each of our results were completely different from Lindsay’s (although our 3 sets of non-local Tampa results all matched). Digging deeper, it turns out that Lindsay is out in the burbs a bit, and her results tended to be more local to her area. The rest of us are located closer to the city centers.

Local SEO Implications

If you’re a city dweller, the results were fairly promising. It seems that Google is taking the location setting at face value and not adding much personalization into the mix. Even though we had logged out, anecdotal evidence suggested that logged in results were similar. The good news is that the "Change Location" feature should be a useful tool for SEOs who do a lot of local work with clients in other cities. Of course, it never hurts to sanity-check your results in any given situation.

One Last Oddity

The latest Google SERPs seem to be integrating organic and local results in some cases, and I suspect that a domain’s overall authority could be impacting the placement of their local result. In our mini-experiment, the Seattle/"coffee" results exhibited an odd behavior, as shown in the screenshot below:

The Starbucks "local" listing appears in the #1 spot, even though the second local listing isn’t until #4. This seems to be a factor of Starbucks’ overall authority. If I change my location back to Chicago, Starbucks is still #1, but I see a local Starbucks address.

It’s clear that a lot is changing in local search, and I think we can expect to see more integration of the overall organic and local algorithms (while local retains some unique factors, like citations and reviews). Whatever happens, though, the new "Change Location" tool seems to be a real window into the local algorithm and should be a welcome addition for local SEOs.